Thesis Abstract

Abstract
The integration of artificial intelligence (AI) technologies in recruitment and selection processes has been a transformative development in the field of Human Resource Management. This thesis explores the impact of AI on recruitment and selection processes in organizations, investigating the benefits, challenges, and implications of this technological advancement. The study aims to provide insights into how AI is reshaping traditional HR practices and influencing decision-making in talent acquisition. The research begins with an exploration of the theoretical background and rationale for incorporating AI in recruitment and selection processes. It examines the evolution of AI technologies in HRM and the potential advantages they offer in streamlining recruitment processes, enhancing candidate experience, and improving decision accuracy. The study also delves into the ethical considerations and concerns surrounding the use of AI in HR practices, such as bias, privacy, and transparency issues. Through a comprehensive literature review, the thesis presents a synthesis of existing research on the impact of AI on recruitment and selection processes. The review covers key topics such as AI-powered talent sourcing, resume screening, candidate assessment, and predictive analytics in recruitment. It highlights the potential of AI to revolutionize HR practices by enabling data-driven decision-making, reducing human bias, and improving the efficiency of talent acquisition processes. The research methodology section outlines the approach taken to investigate the impact of AI on recruitment and selection processes. The study employs a mixed-methods research design, incorporating both qualitative and quantitative data collection methods. Surveys, interviews, and case studies are used to gather insights from HR professionals, recruiters, and job applicants to understand their perspectives on AI adoption in recruitment. The findings of the study reveal the significant impact of AI on recruitment and selection processes in organizations. AI technologies have been found to enhance the efficiency and effectiveness of talent acquisition by automating routine tasks, identifying top candidates, and improving the accuracy of hiring decisions. However, challenges such as algorithmic bias, data privacy concerns, and resistance to change remain key barriers to the widespread adoption of AI in HR practices. In conclusion, this thesis provides a comprehensive analysis of the impact of artificial intelligence on recruitment and selection processes in organizations. It underscores the transformative potential of AI technologies in reshaping HR practices and improving the quality of talent acquisition. The study offers practical implications for HR practitioners, organizational leaders, and policymakers seeking to leverage AI for strategic talent management. Keywords Artificial intelligence, Recruitment, Selection, Human Resource Management, Technology, Talent Acquisition, Data Analytics, Decision-making.

Thesis Overview